Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Artificial neural network +Data clustering +Ulrike von Luxburg +Jupyter/notebook +scikit-learn -Poker +tfidf -tf-idf"

Positive matches

• 0.210 + - Machine learning
• 0.108 + - Class imbalance
• 0.029 + - Deep learning
• 0.026 + - IPython notebook
• 0.024 + - Gradient descent
• 0.023 + - Decision tree
• 0.022 + - Recommender system
• 0.022 + - Brain network
• 0.014 + - Artemy Kolchinsky
• 0.013 + - Jupyter
• 0.013 + - IPython
• 0.012 + - Random forest
• 0.011 + - skorch
• 0.011 + - Boosting (machine learning)
• 0.011 + - Python/Modules
• 0.011 + - Python
• 0.009 + - Tim Hopper
• 0.009 + - Data science
• 0.008 + - Learning
• 0.007 + - SSH tunneling

Negative matches

• 0.024 + - Text analysis
• 0.014 + - Pointwise mutual information
• 0.012 + - Gensim
• 0.012 + - NLTK
• 0.005 + - Natural language processing
• 0.004 + - Lexical feature selection
• 0.003 + - Data analysis
• 0.002 + - word2vec
• 0.001 + - Biomedical natural language processing
• 0.001 + - Skip-gram
• 0.001 + - GloVe
• 0.001 + - StanfordNLP
• 0.001 + - Paper/Levy2014a
• 0.000 + - CPython
• 0.000 + - Tomas Mikolov
• 0.000 + - Omer Levy
• 0.000 + - Paper/Levy2014
• 0.000 + - WordRank
• 0.000 + - Paper
• 0.000 + - Attention (Deep learning)